Prediction Method based DRSA to Improve the Individual Knowledge Appropriation in a Collaborative Learning Environment: Case of MOOCs

Sarra Bouzayane (1) , Inès Saad (1)

1 MIS - Modélisation, Information et Systèmes - UR UPJV 4290

This paper proposes a prediction method that relies on the Dominance-based Rough Set Approach (DRSA) to improve the individual knowledge appropriation when the learning process occurs in a collaborative environment such as the Massive Open Online Courses (MOOCs). This method is based on two phases: the first has to be applied at the end of each week of the MOOC and aims at inferring a preference model resulting in a set of decision rules; the second is applied at the beginning of each week of the same MOOC and consists of classifying each learner in one of the three defined decision

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]

Sarra Bouzayane, Inès Saad. Prediction Method based DRSA to Improve the Individual Knowledge Appropriation in a Collaborative Learning Environment: Case of MOOCs. 50th Hawaii International Conference on System Sciences (HICSS), Jan 2017, Hawaii, United States. pp.124-133. ⟨hal-01796303⟩